DESeq2. Multi-factor Interactions designs

Question

[adR]

Dear all, I want to get your feedback, please !!

I have gene expression data from two tissue(Tissue_1 and Tissue_2) in three conditions(A, B and C). I want to get genes upregulated in Tissue_2 in condition C vs A+B. I was trying this, but not sure if I am correct.

dds <- makeExampleDESeqDataSet(n = 1000, m = 12, betaSD = 2)
dds$tissue <- factor(rep(c("Tissue_1", "Tissue_2"), each = 6))
dds$condition <- factor(rep(c("A", "B", "C"), each = 4))
dds$BC <- factor(dds$condition %in% c("B", "C"))
colData(dds)

dds <- dds[, order(dds$tissue, dds$BC)]
dds$group <- factor(paste0(dds$tissue, dds$BC))
design(dds) <- ~ group
dds <- DESeq(dds)
resultsNames(dds)

best, amare

[Marco Pannone]

Just add one more column in your coldata and name it "comparison2". Then, in the rows corresponding to Tissue 2 condition C you write "2C" and in the rows corresponding to both Tissue 2 conditions A and B you write "2AB" (for example).

Then:

dds$comparison2 <- relevel(dds$comparison2, ref = "2AB")
dds <- DESeq(dds)
resultsNames(dds)
res <- results(dds, name="comparison2_2C_vs_2AB")